1. Technical Field
The present invention relates to image segmentation, and more particularly to a system and method for finding a multi-label image segmentation based on a specification of labels for pixels.
2. Discussion of Related Art
Segmentation is an important component of many clinical medical imaging applications, including anatomic analysis and modeling, morphological measurement, visualization, and surgical planning. Unfortunately, segmentation is often a challenging problem due to difficulties resulting from noise, limited contrast, and weak boundaries often observed in medical images.
Addressing multi-label image segmentation without recursively applied binary segmentation has been proposed using automated and semi-automated methods. Such random walker methods have been shown to perform better than other segmentation algorithms known to-date. However, the random walker methods are limited by calculation time.
Methods for GPU acceleration of image segmentation have been proposed. However, these methods have disadvantages including leaking of a segmentation through a weak boundary, poor performance in cases where pixel intensities are not clearly divided by a threshold, failure to located object boundaries, etc.
Therefore, a need exists for a system and method for accelerating the performance of a random walker method using a GPU implementation, achieving interactive rates.